OSCR

Exploring EEG and ECG in Music Listening: A Scoping Review.

Code ↔ Paper

4 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 4 matches
  1. [1] § Methods › Information Sources ↔ tooling/build_metadata.py, lines 49–143 · score 0.93 · Academic Search Complete, EBSCOhost, PsycArticles, PsycInfo, citation searching, Pubmed
  2. [2] § Results › Publication Information › Region ↔ mcp/psyp70385-mcp/server.py, lines 71–96 · score 0.86 · South Asia, Southeast Asia, North America, Western Europe
  3. [3] § Methods › Search Strategy ↔ tooling/build_metadata.py, lines 49–143 · score 0.64 · PsycArticles, PsycInfo, S2, database, electroencephalography, ECG
  4. [4] § Methods › Eligibility Criteria ↔ mcp/psyp70385-mcp/server.py, lines 247–284 · score 0.60 · peer reviewed journal, English, abstracts, protocols, Eligibility

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

Python · 147 lines · 7.2 KB · MIT · 2 matches

  1. #!/usr/bin/env python3
  2. """Build the small, hand-curated metadata JSON files the MCP server reads
  3. alongside data/studies.json:
  5. data/review_metadata.json citation, ids, links, licence, PRISMA counts
  6. data/eligibility.json Appendix S1 (PCC framework) + the 6 numbered
  7. inclusion/exclusion rules from section 2.2
  8. data/search_strings.json Appendix S2 (per-database search strings)
  9. data/charting_items.json Appendix S3 (the data-charting template)
  10. data/table_footnotes.json per-table footnote letter -> meaning, so a
  11. "^a" marker on a cell can be resolved
  13. Source text is extracted from the reading package (references/paper.md,
  14. references/supplement.md) and data/tables.json, not retyped, so a change to
  15. either regenerates this file with the same wording.
  16. """
  17. import json
  18. import re
  19. from pathlib import Path
  21. ROOT = Path(__file__).resolve().parents[1]
  22. PKG = ROOT / "dist" / "eeg-ecg-music-review-agent" / "skill" / "psyp70385-eeg-ecg-music-scoping-review-paper"
  23. PAPER_MD = PKG / "references" / "paper.md"
  24. SUPP_MD = PKG / "references" / "supplement.md"
  25. TABLES = ROOT / "data" / "tables.json"
  28. def section(md, start_heading, end_heading=None):
  29. i = md.index(start_heading)
  30. j = md.index(end_heading, i + len(start_heading)) if end_heading else len(md)
  31. return md[i:j].strip()
  34. def numbered_rules(text_):
  35. """Split '2.2 | Eligibility Criteria' body into its 6 numbered paragraphs."""
  36. body = text_.split("\n\n", 2)[-1] # drop the heading and the lead-in sentence
  37. parts = re.split(r"\n\n(?=\d+\. )", body)
  38. rules = []
  39. for p in parts:
  40. m = re.match(r"^(\d+)\. (.+)$", p, flags=re.S)
  41. if not m:
  42. continue
  43. rules.append({"rule": int(m.group(1)), "text": re.sub(r"\s+", " ", m.group(2)).strip()})
  44. if len(rules) != 6:
  45. raise SystemExit(f"expected 6 eligibility rules, parsed {len(rules)}")
  46. return rules
  49. def main():
  50. paper_md = PAPER_MD.read_text(encoding="utf-8")
  51. supp_md = SUPP_MD.read_text(encoding="utf-8")
  52. tables = json.loads(TABLES.read_text(encoding="utf-8"))
  54. # --- eligibility.json ---------------------------------------------
  55. elig_section = section(paper_md, "### 2.2 | Eligibility Criteria", "### 2.3")
  56. rules = numbered_rules(elig_section)
  57. appendix_s1 = section(supp_md, "## Appendix S1")
  58. eligibility = {
  59. "source": "Section 2.2 (Eligibility Criteria) and Appendix S1 (Framework) of Leimroth et al. 2026, doi:10.1111/psyp.70385",
  60. "inclusion_exclusion_rules": rules,
  61. "pcc_framework_markdown": appendix_s1,
  62. }
  63. (ROOT / "data" / "eligibility.json").write_text(json.dumps(eligibility, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
  65. # --- search_strings.json --------------------------------------------
  66. appendix_s2 = section(supp_md, "## Appendix S2")
  67. search = {
  68. "source": "Appendix S2 (Search Details) of Leimroth et al. 2026, doi:10.1111/psyp.70385",
  69. "databases": ["PsycInfo (including PsycArticles)", "PubMed", "Scopus", "Web of Science (core collection)", "Academic Search Complete (EBSCOhost)"],
  70. "initial_search_date": "2024-01-31",
  71. "update_search_date": "2025-08-10",
  72. "citation_searching_records": 10,
  73. "search_strings_markdown": appendix_s2,
  74. }
  75. (ROOT / "data" / "search_strings.json").write_text(json.dumps(search, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
  77. # --- charting_items.json ---------------------------------------------
  78. appendix_s3 = section(supp_md, "## Appendix S3")
  79. charting = {
  80. "source": "Appendix S3 (Data Items) of Leimroth et al. 2026, doi:10.1111/psyp.70385",
  81. "categories": {
  82. "publication_information": ["Author/Year", "Region", "Aim of Study", "Findings"],
  83. "participants": ["Audiology", "Musicianship", "Handedness", "Eligibility Criteria", "Sample Size", "Final Number Processed", "Sex", "Age"],
  84. "measures": {
  85. "eeg": ["Variables", "Electrode Configuration", "Electrode Type", "Impedance", "Referencing", "Filtering", "Hardware", "Sampling Frequency"],
  86. "ecg": ["Variables", "Electrode Configuration", "Recording Equipment", "Filtering", "Sampling Rate", "Blood Pressure/Respiration"],
  87. },
  88. "experimental_conditions": {
  89. "stimulus": ["Duration", "Musical Component Examined", "Style", "Source", "Delivery Method", "Intensity", "Selection", "Familiarity", "Attention to Stimulus"],
  90. "study_design": ["Hypothesis", "Room Details", "Time of Day", "Orientation", "Visual State", "Control/Baseline", "Power Analysis", "Ethics/Informed Consent"],
  91. },
  92. },
  93. "template_markdown": appendix_s3,
  94. }
  95. (ROOT / "data" / "charting_items.json").write_text(json.dumps(charting, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
  97. # --- table_footnotes.json --------------------------------------------
  98. footnotes = {}
  99. for t in tables:
  100. n = int(t["label"].split()[1])
  101. entries = {}
  102. for note in t["notes"]:
  103. m = re.match(r"^([a-z])\s+(.+)$", note, flags=re.S)
  104. if m:
  105. entries[m.group(1)] = m.group(2).strip()
  106. if entries:
  107. footnotes[str(n)] = entries
  108. (ROOT / "data" / "table_footnotes.json").write_text(json.dumps(footnotes, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
  110. # --- review_metadata.json ---------------------------------------------
  111. metadata = {
  112. "citation": "Leimroth, S. R., Barry, R. J., De Blasio, F. M., & Byron, T. P. (2026). Exploring EEG and ECG in music listening: A scoping review. Psychophysiology, 63(9), e70385.",
  113. "doi": "10.1111/psyp.70385",
  114. "pubmed_id": "42693627",
  115. "pmc_id": "PMC13542476",
  116. "published_online": "2026-09-03",
  117. "received": "2026-05-18",
  118. "revised": "2026-08-18",
  119. "accepted": "2026-08-19",
  120. "licence": "CC BY 4.0",
  121. "open_access_pdf": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/psyp.70385",
  122. "preregistration": {"protocol": "https://osf.io/yx3rh", "project": "https://osf.io/xtznm"},
  123. "orcid": "0000-0003-3617-7994",
  124. "affiliation": "Brain & Behaviour Research Institute and School of Psychology, University of Wollongong",
  125. "methodology": ["Joanna Briggs Institute scoping review methodology", "PRISMA-ScR"],
  126. "prisma_flow": {
  127. "identified": 1214,
  128. "duplicates_removed": 596,
  129. "screened": 618,
  130. "excluded_at_screening": 581,
  131. "sought_for_retrieval": 37,
  132. "not_retrieved": 0,
  133. "assessed_for_eligibility": 37,
  134. "excluded_at_eligibility": 19,
  135. "included": 18,
  136. },
  137. "included_studies": 18,
  138. "first_authors": 13,
  139. "data_availability": "This scoping review did not generate or analyze primary experimental data; no original data or analysis code is associated with the manuscript.",
  140. }
  141. (ROOT / "data" / "review_metadata.json").write_text(json.dumps(metadata, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
  143. print("wrote data/eligibility.json, data/search_strings.json, data/charting_items.json, data/table_footnotes.json, data/review_metadata.json")
  146. if __name__ == "__main__":
  147. main()

build_metadata.py at commit 5c1f99f, under MIT · at the source

Overview

Authors: Scott R Leimroth1, Robert J Barry1, Frances M De Blasio1, Timothy P Byron1
ORCID iDs: Scott R Leimroth, Robert J Barry, Frances M De Blasio, Timothy P Byron
  1. Brain & Behaviour Research Institute and School of Psychology, University of Wollongong, Wollongong, New South Wales, Australia
Institutions: University of Wollongong (Australia)
Journal: Psychophysiology, volume 63, issue 9, article e70385
Dates: received 18 May 2026; accepted 19 August 2026; published online 3 September 2026; in print September 2026
Type: Review · Language: English
License: CC BY
Identifiers: DOI 10.1111/psyp.70385 · PMID 42693627 · PMCID PMC13542476 · OpenAlex W7208744105
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: EEG (modality), other (modality), human (organism), cognitive (subfield)
Methods: Evoked potentials
Keywords: ECG, EEG, guidelines, methodology, music listening, scoping review
MeSH: Auditory Perception*, Brain*, Electrocardiography*, Electroencephalography*, Evoked Potentials*, Heart Rate*, Music*, Humans (* major topic)
Topic: Music Therapy and Health (Social Psychology, Psychology), according to OpenAlex
Funding: Australian Government; University of Wollongong
Citations: not cited yet (Europe PMC); 173 references in the paper

Abstract

Music listening, a common daily activity recognized for its emotional impact and ability to evoke memories, engages physiological and psychological processes. Concurrent electroencephalography (EEG) and electrocardiography (ECG) during music listening can inform our understanding of these processes. However, the insights offered by such simultaneous recordings, and the extent to which existing studies align with published methodological guidelines, remain unclear. To address this gap, we conducted a scoping review of peer‐reviewed research examining physiological responses to passive music listening using combined EEG and ECG measures in healthy adult non‐musicians. A structured search of five databases identified 18 papers. Data on methods, participant demographics, musical stimuli, and EEG/ECG measures were extracted and compared against established guidelines to clarify the studies' methodological rigor. EEG findings were highly heterogeneous, spanning spectral power, lateralized effects, and event‐related potentials, with limited overlap in analytical focus. Cardiac outcomes were similarly mixed, with studies reporting increases, decreases, or no change in heart rate depending on stimulus and context. Only a small subset of studies examined brain‐heart coupling directly, with preliminary evidence of synchronization between neural and cardiac rhythms during music listening, leaving the central question of how brain and heart respond together to music largely open. Our review identified significant methodological inconsistencies and a lack of integration between the two measures, highlighting the challenges of this interdisciplinary research. Advancing research in both music and psychophysiology requires improving alignment between methodologies from these distinct areas by following established standards. These findings highlight a critical need for greater methodological standardization to build a more reliable and replicable understanding of music's psychophysiological effects.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above, with 4 matches between paragraphs and lines of code.

Zenodo 22827658

License: MIT
State: the link answers, verified on 26 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: DataCite
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 26 September 2026: the link answers (HTTP 200)
  • 26 September 2026: the link answers (HTTP 200)
12 files
At the source: doi.org/10.5281/zenodo.22827658

scottleimroth/eeg-ecg-music-review-agent

License: MIT
State: the link answers, verified on 26 September 2026
Evidence: files inventoried
Commit: 5c1f99f8376ac07c20ac253b83d1c3c7d5d82e0e, 18 September 2026
Languages: Python (9)
Size: 34 files, 9 scripts
Software Heritage: not archived
Found in: DataCite
Holds: README, license file, tests
Not found: CITATION.cff, environment file, continuous integration, documentation
Availability: 1 check, the latest on 26 September 2026: the link answers
  • 26 September 2026: the link answers
12 files
At the source: github.com/scottleimroth/eeg-ecg-music-review-agent/tree/V1.0.0

Zenodo 22827659

License: MIT
State: the link answers, verified on 26 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: DataCite
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 26 September 2026: the link answers (HTTP 200)
  • 26 September 2026: the link answers (HTTP 200)
12 files
At the source: doi.org/10.5281/zenodo.22827659

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 3 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 27 scripts, each with its path and the digest of its content;
  • 4 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data Availability Statement

This scoping review did not generate or analyze primary experimental data; no original data or analysis code is associated with the manuscript. The review protocol was preregistered on the Open Science Framework at https://osf.io/yx3rh (associated project https://osf.io/xtznm). Full search strategies, eligibility criteria, and data‐charting items are reported in Appendices S1–, S3, and all data charted from the included studies are presented in the manuscript and Appendices S1–, S3.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 3, 28 September 2026

  • Publisher: n/a → Wiley
  • Funding: added Australian Government; University of Wollongong

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 6 keywords, 8 MeSH terms, 160 references.

Cite

This paper

Leimroth, S. R., Barry, R. J., De Blasio, F. M., & Byron, T. P. (2026). Exploring EEG and ECG in Music Listening: A Scoping Review. Psychophysiology, 63(9), e70385. https://doi.org/10.1111/psyp.70385

BibTeX

@article{leimroth2026exploring,
author = {Leimroth, Scott R and Barry, Robert J and De Blasio, Frances M and Byron, Timothy P},
title = {{Exploring EEG and ECG in Music Listening: A Scoping Review}},
journal = {Psychophysiology},
year = {2026},
month = sep,
volume = {63},
number = {9},
pages = {e70385},
publisher = {Wiley},
issn = {0048-5772},
doi = {10.1111/psyp.70385},
url = {https://doi.org/10.1111/psyp.70385},
pmid = {42693627},
pmcid = {PMC13542476}
}

RIS

TY - JOUR
AU - Leimroth, Scott R
AU - Barry, Robert J
AU - De Blasio, Frances M
AU - Byron, Timothy P
TI - Exploring EEG and ECG in Music Listening: A Scoping Review
T2 - Psychophysiology
J2 - Psychophysiology
PY - 2026
DA - 2026/09/01
VL - 63
IS - 9
SP - e70385
SN - 0048-5772
PB - Wiley
DO - 10.1111/psyp.70385
UR - https://doi.org/10.1111/psyp.70385
LA - en
ER -

CSL-JSON

{
"id": "10.1111/psyp.70385",
"type": "article-journal",
"title": "Exploring EEG and ECG in Music Listening: A Scoping Review",
"container-title": "Psychophysiology",
"author": [
{
"family": "Leimroth",
"given": "Scott R"
},
{
"family": "Barry",
"given": "Robert J"
},
{
"family": "De Blasio",
"given": "Frances M"
},
{
"family": "Byron",
"given": "Timothy P"
}
],
"container-title-short": "Psychophysiology",
"volume": "63",
"issue": "9",
"page": "e70385",
"DOI": "10.1111/psyp.70385",
"PMID": "42693627",
"PMCID": "PMC13542476",
"ISSN": "0048-5772",
"publisher": "Wiley",
"URL": "https://doi.org/10.1111/psyp.70385",
"language": "en",
"issued": {
"date-parts": [
[
2026,
9,
1
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1111/psyp.70297 [code]
Heartbeat-Evoked Responses in M/EEG: A Systematic Review of Methods With Suggestions for Analysis and Reporting.
Journal: Psychophysiology
In common: EEG, 8 references
[2] doi:10.1038/s41598-026-52930-9
Cardiac systole is associated with enhanced go responding in an orthogonalized go/nogo task.
Journal: Scientific reports
In common: cognitive, 6 references
[3] doi:10.1162/imag.a.1353 [code]
Model-based cardiac field artefact correction for OP-MEG.
Journal: Imaging neuroscience (Cambridge, Mass.)
In common: EEG, 6 references
[4] doi:10.1093/nc/niag009 [code]
Autonomic indicators of self-transcendence: insights from the numadelic VR paradigm.
Journal: Neuroscience of consciousness
In common: cognitive, 4 references
[5] doi:10.1162/imag.a.1325 [code]
Decoding everyday levels of musical training from subcortical white-matter architecture.
Journal: Imaging neuroscience (Cambridge, Mass.)
In common: 4 references
[6] doi:10.3389/fnsys.2026.1880737
Autonomic-salience stability as a candidate Gate for awake low-dose ketamine: a systems neuroscience framework with a clinical anchor.
Journal: Frontiers in systems neuroscience
In common: other, 3 references
[7] doi:10.1002/mdc3.70734
A Randomized Controlled Trial of Dual Upper-Extremity Training [DUET]: Combining Neurologic Music Therapy® with Noninvasive Brain Stimulation for Upper-Limb Performance in Corticobasal Syndrome.
Journal: Movement disorders clinical practice
In common: other, 3 references
[8] doi:10.1162/imag.a.1319 [code]
When the inner clock fades: Interoceptive decline and consolidation of phase resetting in cortical rhythms by cardiac events underlie healthy lifespan aging.
Journal: Imaging neuroscience (Cambridge, Mass.)
In common: cognitive, 3 references
[9] doi:10.1111/psyp.70301
Oscillatory Markers of Interoceptive Attention: Beta Suppression as a Neural Signature of Heartbeat Processing.
Journal: Psychophysiology
In common: cognitive, 3 references
[10] doi:10.1016/j.dcn.2026.101741
Pediatric resting EEG collection, preprocessing, and analysis: A systematic review.
Journal: Developmental cognitive neuroscience
In common: EEG, 3 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.